{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset</th>\n",
       "      <th>Data Types</th>\n",
       "      <th>Default Task</th>\n",
       "      <th>Target Variable</th>\n",
       "      <th># Instances</th>\n",
       "      <th># Attributes</th>\n",
       "      <th>Missing Values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>cancer</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>Class</td>\n",
       "      <td>683</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>credit</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>default</td>\n",
       "      <td>24000</td>\n",
       "      <td>24</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>employee</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>left</td>\n",
       "      <td>14999</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>heart</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>DEATH</td>\n",
       "      <td>200</td>\n",
       "      <td>17</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>hepatitis</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>Class</td>\n",
       "      <td>154</td>\n",
       "      <td>32</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>income</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>income &gt;50K</td>\n",
       "      <td>32561</td>\n",
       "      <td>14</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>iris</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>Class</td>\n",
       "      <td>100</td>\n",
       "      <td>5</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>juice</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>Purchase</td>\n",
       "      <td>1070</td>\n",
       "      <td>15</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>heart_disease</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Classification</td>\n",
       "      <td>Disease</td>\n",
       "      <td>270</td>\n",
       "      <td>14</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>glass</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Multiclass Classification</td>\n",
       "      <td>Type</td>\n",
       "      <td>214</td>\n",
       "      <td>10</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>satellite</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Multiclass Classification</td>\n",
       "      <td>Class</td>\n",
       "      <td>6435</td>\n",
       "      <td>37</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>poker</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Multiclass Classification</td>\n",
       "      <td>CLASS</td>\n",
       "      <td>100000</td>\n",
       "      <td>11</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>automobile</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Regression</td>\n",
       "      <td>price</td>\n",
       "      <td>202</td>\n",
       "      <td>26</td>\n",
       "      <td>Y</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>bike</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Regression</td>\n",
       "      <td>cnt</td>\n",
       "      <td>17379</td>\n",
       "      <td>15</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>boston</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Regression</td>\n",
       "      <td>medv</td>\n",
       "      <td>506</td>\n",
       "      <td>14</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>diamond</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Regression</td>\n",
       "      <td>Price</td>\n",
       "      <td>6000</td>\n",
       "      <td>8</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>gold</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Regression</td>\n",
       "      <td>Gold_T+22</td>\n",
       "      <td>2558</td>\n",
       "      <td>121</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>tweets</td>\n",
       "      <td>Text</td>\n",
       "      <td>NLP</td>\n",
       "      <td>tweet</td>\n",
       "      <td>8594</td>\n",
       "      <td>2</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>amazon</td>\n",
       "      <td>Text</td>\n",
       "      <td>NLP / Classification</td>\n",
       "      <td>reviewText</td>\n",
       "      <td>20000</td>\n",
       "      <td>2</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>kiva</td>\n",
       "      <td>Text</td>\n",
       "      <td>NLP / Classification</td>\n",
       "      <td>en</td>\n",
       "      <td>6818</td>\n",
       "      <td>7</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>spx</td>\n",
       "      <td>Text</td>\n",
       "      <td>NLP / Regression</td>\n",
       "      <td>text</td>\n",
       "      <td>874</td>\n",
       "      <td>4</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>germany</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Association Rule Mining</td>\n",
       "      <td>InvoiceNo, Description</td>\n",
       "      <td>9495</td>\n",
       "      <td>8</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>france</td>\n",
       "      <td>Multivariate</td>\n",
       "      <td>Association Rule Mining</td>\n",
       "      <td>InvoiceNo, Description</td>\n",
       "      <td>8557</td>\n",
       "      <td>8</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Dataset    Data Types               Default Task  \\\n",
       "0          cancer  Multivariate             Classification   \n",
       "1          credit  Multivariate             Classification   \n",
       "2        employee  Multivariate             Classification   \n",
       "3           heart  Multivariate             Classification   \n",
       "4       hepatitis  Multivariate             Classification   \n",
       "5          income  Multivariate             Classification   \n",
       "6            iris  Multivariate             Classification   \n",
       "7           juice  Multivariate             Classification   \n",
       "8   heart_disease  Multivariate             Classification   \n",
       "9           glass  Multivariate  Multiclass Classification   \n",
       "10      satellite  Multivariate  Multiclass Classification   \n",
       "11          poker  Multivariate  Multiclass Classification   \n",
       "12     automobile  Multivariate                 Regression   \n",
       "13           bike  Multivariate                 Regression   \n",
       "14         boston  Multivariate                 Regression   \n",
       "15        diamond  Multivariate                 Regression   \n",
       "16           gold  Multivariate                 Regression   \n",
       "17         tweets          Text                        NLP   \n",
       "18         amazon          Text       NLP / Classification   \n",
       "19           kiva          Text       NLP / Classification   \n",
       "20            spx          Text           NLP / Regression   \n",
       "21        germany  Multivariate    Association Rule Mining   \n",
       "22         france  Multivariate    Association Rule Mining   \n",
       "\n",
       "           Target Variable  # Instances  # Attributes Missing Values  \n",
       "0                    Class          683            10              N  \n",
       "1                  default        24000            24              N  \n",
       "2                     left        14999            10              N  \n",
       "3                    DEATH          200            17              N  \n",
       "4                    Class          154            32              Y  \n",
       "5              income >50K        32561            14              Y  \n",
       "6                    Class          100             5              N  \n",
       "7                 Purchase         1070            15              N  \n",
       "8                  Disease          270            14              N  \n",
       "9                     Type          214            10              N  \n",
       "10                   Class         6435            37              N  \n",
       "11                   CLASS       100000            11              N  \n",
       "12                   price          202            26              Y  \n",
       "13                     cnt        17379            15              N  \n",
       "14                    medv          506            14              N  \n",
       "15                   Price         6000             8              N  \n",
       "16               Gold_T+22         2558           121              N  \n",
       "17                   tweet         8594             2              N  \n",
       "18              reviewText        20000             2              N  \n",
       "19                      en         6818             7              N  \n",
       "20                    text          874             4              N  \n",
       "21  InvoiceNo, Description         9495             8              N  \n",
       "22  InvoiceNo, Description         8557             8              N  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pycaret.datasets import get_data\n",
    "get_data('index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Purchase</th>\n",
       "      <th>StoreID</th>\n",
       "      <th>PriceCH</th>\n",
       "      <th>PriceMM</th>\n",
       "      <th>DiscCH</th>\n",
       "      <th>DiscMM</th>\n",
       "      <th>SpecialCH</th>\n",
       "      <th>SpecialMM</th>\n",
       "      <th>LoyalCH</th>\n",
       "      <th>SalePriceMM</th>\n",
       "      <th>SalePriceCH</th>\n",
       "      <th>PriceDiff</th>\n",
       "      <th>PctDiscMM</th>\n",
       "      <th>PctDiscCH</th>\n",
       "      <th>ListPriceDiff</th>\n",
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       "      <td>1.69</td>\n",
       "      <td>1.75</td>\n",
       "      <td>-0.06</td>\n",
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       "      <td>0.24</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.09</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.69</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.091398</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.400000</td>\n",
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       "      <td>1.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.956535</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Purchase  StoreID  PriceCH  PriceMM  DiscCH  DiscMM  SpecialCH  SpecialMM  \\\n",
       "0         1        1     1.75     1.99    0.00     0.0          0          0   \n",
       "1         1        1     1.75     1.99    0.00     0.3          0          1   \n",
       "2         1        1     1.86     2.09    0.17     0.0          0          0   \n",
       "3         0        1     1.69     1.69    0.00     0.0          0          0   \n",
       "4         1        7     1.69     1.69    0.00     0.0          0          0   \n",
       "\n",
       "    LoyalCH  SalePriceMM  SalePriceCH  PriceDiff  PctDiscMM  PctDiscCH  \\\n",
       "0  0.500000         1.99         1.75       0.24   0.000000   0.000000   \n",
       "1  0.600000         1.69         1.75      -0.06   0.150754   0.000000   \n",
       "2  0.680000         2.09         1.69       0.40   0.000000   0.091398   \n",
       "3  0.400000         1.69         1.69       0.00   0.000000   0.000000   \n",
       "4  0.956535         1.69         1.69       0.00   0.000000   0.000000   \n",
       "\n",
       "   ListPriceDiff  \n",
       "0           0.24  \n",
       "1           0.24  \n",
       "2           0.23  \n",
       "3           0.00  \n",
       "4           0.00  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = get_data('juice')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pycaret.anomaly import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
       "                        <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row0_col1\" class=\"data row0 col1\" >3381</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row1_col0\" class=\"data row1 col0\" >Scaling</td>\n",
       "                        <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row1_col1\" class=\"data row1 col1\" >True</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row2_col0\" class=\"data row2 col0\" >Shape</td>\n",
       "                        <td id=\"T_187456d2_3286_11ea_b6d3_84fdd13f47d7row2_col1\" class=\"data row2 col1\" >(1070, 15)</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x25955aefa48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = setup(data, normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn = create_model('knn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.956535</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.605170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1065</th>\n",
       "      <td>7</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.09</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.587822</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.76</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.053763</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.087822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1066</th>\n",
       "      <td>7</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.670258</td>\n",
       "      <td>2.18</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.009742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>7</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.736206</td>\n",
       "      <td>2.18</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.030322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>7</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.13</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.588965</td>\n",
       "      <td>1.89</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.112676</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.123329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1069</th>\n",
       "      <td>1</td>\n",
       "      <td>1.86</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.671172</td>\n",
       "      <td>2.18</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.32</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.195012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1070 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      StoreID  PriceCH  PriceMM  DiscCH  DiscMM  SpecialCH  SpecialMM  \\\n",
       "0           1     1.75     1.99    0.00    0.00          0          0   \n",
       "1           1     1.75     1.99    0.00    0.30          0          1   \n",
       "2           1     1.86     2.09    0.17    0.00          0          0   \n",
       "3           1     1.69     1.69    0.00    0.00          0          0   \n",
       "4           7     1.69     1.69    0.00    0.00          0          0   \n",
       "...       ...      ...      ...     ...     ...        ...        ...   \n",
       "1065        7     1.86     2.09    0.10    0.00          0          0   \n",
       "1066        7     1.86     2.18    0.00    0.00          0          0   \n",
       "1067        7     1.86     2.18    0.00    0.00          0          0   \n",
       "1068        7     1.86     2.13    0.00    0.24          0          0   \n",
       "1069        1     1.86     2.18    0.00    0.00          0          0   \n",
       "\n",
       "       LoyalCH  SalePriceMM  SalePriceCH  PriceDiff  PctDiscMM  PctDiscCH  \\\n",
       "0     0.500000         1.99         1.75       0.24   0.000000   0.000000   \n",
       "1     0.600000         1.69         1.75      -0.06   0.150754   0.000000   \n",
       "2     0.680000         2.09         1.69       0.40   0.000000   0.091398   \n",
       "3     0.400000         1.69         1.69       0.00   0.000000   0.000000   \n",
       "4     0.956535         1.69         1.69       0.00   0.000000   0.000000   \n",
       "...        ...          ...          ...        ...        ...        ...   \n",
       "1065  0.587822         2.09         1.76       0.33   0.000000   0.053763   \n",
       "1066  0.670258         2.18         1.86       0.32   0.000000   0.000000   \n",
       "1067  0.736206         2.18         1.86       0.32   0.000000   0.000000   \n",
       "1068  0.588965         1.89         1.86       0.03   0.112676   0.000000   \n",
       "1069  0.671172         2.18         1.86       0.32   0.000000   0.000000   \n",
       "\n",
       "      ListPriceDiff  Purchase  Label     Score  \n",
       "0              0.24         1      0  0.064800  \n",
       "1              0.24         1      0  0.187566  \n",
       "2              0.23         1      0  0.295202  \n",
       "3              0.00         0      0  0.100000  \n",
       "4              0.00         1      1  0.605170  \n",
       "...             ...       ...    ...       ...  \n",
       "1065           0.23         1      0  0.087822  \n",
       "1066           0.32         1      0  0.009742  \n",
       "1067           0.32         0      0  0.030322  \n",
       "1068           0.27         1      0  0.123329  \n",
       "1069           0.32         1      0  0.195012  \n",
       "\n",
       "[1070 rows x 17 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tuned_df"
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  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
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       "      <th>crim</th>\n",
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       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
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       "      <td>17.8</td>\n",
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       "      <td>4.03</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>5.33</td>\n",
       "      <td>36.2</td>\n",
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      "text/plain": [
       "      crim    zn  indus  chas    nox     rm   age     dis  rad  tax  ptratio  \\\n",
       "0  0.00632  18.0   2.31     0  0.538  6.575  65.2  4.0900    1  296     15.3   \n",
       "1  0.02731   0.0   7.07     0  0.469  6.421  78.9  4.9671    2  242     17.8   \n",
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       "4  0.06905   0.0   2.18     0  0.458  7.147  54.2  6.0622    3  222     18.7   \n",
       "\n",
       "    black  lstat  medv  \n",
       "0  396.90   4.98  24.0  \n",
       "1  396.90   9.14  21.6  \n",
       "2  392.83   4.03  34.7  \n",
       "3  394.63   2.94  33.4  \n",
       "4  396.90   5.33  36.2  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = get_data('boston')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "                                <td id=\"T_d8ea8690_32a3_11ea_9d3d_84fdd13f47d7row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
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   "outputs": [],
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